3 Best Practices for Creating an Effective Data Strategy

Executive Blog
Written by Amitabh Seli, CDAO, Director Data UK, Danone

Amitabh Seli

CDAO, Director Data UK


MAY 21, 2024

Establishing and retaining a solid data and analytics strategy is a top priority for Chief Data & Analytics Officers (CDAOs) in Evanta CDAO communities around the world. In fact, in our annual Leadership Perspective Survey of community members, data and analytics strategy ranks number two in data leaders’ functional priorities for 2024. 

Since this is a critical priority for CDAOs, we asked Governing Body Member Amitabh Seli, CDAO, Director Data UK at Danone, to share his experience in establishing a data strategy that is aligned to the business strategy and helps demonstrate the value of data to the organisation.

Amitabh is a commercial minded leader experienced in enabling large businesses to become data led. He has created and managed large transformation projects to help brands grow, drive consumer centricity and improve profitability. Amitabh led large, cross-functional internal and external teams to create products and platforms that empower teams to drive performance, impact and efficiency. He is a trusted advisor to boards, adept in influencing investment and customer decisions. Amitabh is also a Governing Body Member of the UK & Ireland CDAO Community.

Here, Amitabh shares some key learnings and best practices in building and implementing your data strategy and how setting a strong foundation is essential to your AI initiatives.

Tell us why you think having a strong data strategy is so important. Was there an experience in your career that illustrated the importance of data strategy?

Data strategy underpins and drives the business agenda through data and analytics. A well-defined data strategy encompasses technology, processes, people, and governance to grow an organisation's capability to make better decisions efficiently.

A structured data strategy fuels innovation and minimises risks in the business, which enable it to remain competitive. A good and well-defined data strategy is pinned both to the business strategy and to clear progress milestones.

In my role at an airline, I came across one of the best examples of a data strategy that mirrored the business goals and strategy. This alignment meant agile thinking and teams in data and analytics who were proactively foreseeing challenges in the market through data and collaboration to build proactive solutions, which helped the airline remain competitive.

What are some of the challenges for CDAOs in establishing or implementing their data strategies?

Data leaders will need to be integrated into business operating plans, and as the outcome of that, they should underpin their data strategy on those plans. Trust, business partnering and sharing risks and opportunities openly at the C-level will strongly affect the outcomes and chances of success with a data strategy.

Navigating independent, siloed operating organisations and lack of data literacy should be top priority for CDAOs to plan and overcome in order to build and execute their data strategy.

Tell us about the connection between a good data strategy and demonstrating the value of data to the business.

Business value is the hallmark of a well-constructed data strategy. Strong alignment to the business strategy should naturally deliver and demonstrate business value through data and analytics.

What are 3 best practices for establishing a strong data strategy?

I cannot emphasise enough the importance and clarity of the business strategy. My advice on best practices to building a solid data strategy are:

  1. Co-build rather than share. Build a strong understanding and relationships in the business that allow you deep insights into the business drivers. Once there is business value attached to the drivers, involve the relevant stakeholders to develop a data strategy that solves the business priorities with highest values. This creates trust, transparency and shared belief in the data strategy.
  2. Ensure your strategy is accurately estimated cost-wise and the returns are in-line or higher than the business goals. Establish measurement and governance to track costs, business value and expected SLAs.
  3. Scalability and adaptability are intrinsic to the plan. With market and geo-political volatility, it is vital that the data strategy is resilient and has longevity. This will in turn future proof the organisation, as well.

Transformations that are well understood by organisations at various levels are more likely to be successful.”

What have you learned from leading these transformations that other CDAOs might benefit from?

  • Build trust and engagement with the leadership and key stakeholders. Transformations that are well understood by organisations at various levels, especially across business teams, are more likely to be successful. Build an inclusive program that relies on the data teams to work alongside their business colleagues, so the transformation feels more like a partnership. Encourage collaboration to create data-led innovation and initiatives.
  • Mitigate and plan for risks and changes.
  • Develop and execute the plan with a modular mindset and flexible architecture. Phasing the overall transformation in modules will ensure greater adherence to plan.

What is your current approach to AI or generative AI? How do you think data strategy ties to new or emerging technologies, like AI?

The acceleration of Gen AI has not yet directly led to business adoption. Organisations are cautious, curious and focused on how AI delivers tangible growth and productivity. It is a matter of time before we will start seeing applications being used by the business that deliver against some of the items identified in the data strategy.

Early business engagement is critical to reflect changes in priorities and potential topics to apply AI solutions. These should be reflected in the data strategy. Strong data security and governance will need to precede integration and application of any AI initiatives, especially in light of ethics and hallucination from LLM models.

To learn more from your data and analytics peers and participate in discussions on topics like data strategy and more, find your local Evanta CDAO Community and join today. If you are already a member of an Evanta CDAO community, check out MyEvanta to view upcoming opportunities to collaborate in-person and virtually with your CDAO peers.

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